diff --git a/.basedpyright/baseline.json b/.basedpyright/baseline.json index 43b9e8e8..a61cc64f 100644 --- a/.basedpyright/baseline.json +++ b/.basedpyright/baseline.json @@ -1031,14 +1031,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 31, - "endColumn": 38, - "lineCount": 1 - } - }, { "code": "reportUnknownVariableType", "range": { @@ -1063,14 +1055,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 31, - "endColumn": 38, - "lineCount": 1 - } - }, { "code": "reportUnknownMemberType", "range": { @@ -1105,30 +1089,6 @@ } ], "./grudge/geometry/metrics.py": [ - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 8, - "endColumn": 31, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 42, - "endColumn": 65, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 48, - "endColumn": 64, - "lineCount": 1 - } - }, { "code": "reportArgumentType", "range": { @@ -1139,67 +1099,11 @@ }, { "code": "reportReturnType", - "range": { - "startColumn": 11, - "endColumn": 38, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 45, - "endColumn": 35, - "lineCount": 5 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 45, - "endColumn": 49, - "lineCount": 5 - } - }, - { - "code": "reportUnknownParameterType", - "range": { - "startColumn": 4, - "endColumn": 10, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 11, - "endColumn": 23, - "lineCount": 4 - } - }, - { - "code": "reportUnknownVariableType", "range": { "startColumn": 11, "endColumn": 37, "lineCount": 4 } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 4, - "endColumn": 10, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 13, - "endColumn": 56, - "lineCount": 1 - } } ], "./grudge/interpolation.py": [ @@ -1276,51 +1180,35 @@ } } ], - "./grudge/models/__init__.py": [ - { - "code": "reportImplicitAbstractClass", - "range": { - "startColumn": 6, - "endColumn": 24, - "lineCount": 1 - } - }, + "./grudge/models/advection.py": [ { "code": "reportUnknownParameterType", "range": { - "startColumn": 42, - "endColumn": 46, - "lineCount": 1 - } - }, - { - "code": "reportMissingParameterType", - "range": { - "startColumn": 42, - "endColumn": 46, + "startColumn": 4, + "endColumn": 23, "lineCount": 1 } }, { "code": "reportUnknownParameterType", "range": { - "startColumn": 50, - "endColumn": 56, + "startColumn": 24, + "endColumn": 29, "lineCount": 1 } }, { "code": "reportMissingParameterType", "range": { - "startColumn": 50, - "endColumn": 56, + "startColumn": 24, + "endColumn": 29, "lineCount": 1 } }, { "code": "reportUnknownParameterType", "range": { - "startColumn": 36, + "startColumn": 31, "endColumn": 40, "lineCount": 1 } @@ -1328,7 +1216,7 @@ { "code": "reportMissingParameterType", "range": { - "startColumn": 36, + "startColumn": 31, "endColumn": 40, "lineCount": 1 } @@ -1337,7 +1225,7 @@ "code": "reportUnknownParameterType", "range": { "startColumn": 42, - "endColumn": 47, + "endColumn": 49, "lineCount": 1 } }, @@ -1345,7 +1233,7 @@ "code": "reportMissingParameterType", "range": { "startColumn": 42, - "endColumn": 47, + "endColumn": 49, "lineCount": 1 } }, @@ -1353,7 +1241,7 @@ "code": "reportUnknownParameterType", "range": { "startColumn": 51, - "endColumn": 57, + "endColumn": 59, "lineCount": 1 } }, @@ -1361,337 +1249,183 @@ "code": "reportMissingParameterType", "range": { "startColumn": 51, - "endColumn": 57, + "endColumn": 59, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 21, - "endColumn": 53, + "startColumn": 4, + "endColumn": 8, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 54, - "endColumn": 58, + "startColumn": 11, + "endColumn": 22, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 62, - "endColumn": 68, + "startColumn": 11, + "endColumn": 36, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 8, - "endColumn": 23, + "startColumn": 4, + "endColumn": 6, "lineCount": 1 } }, { - "code": "reportOperatorIssue", + "code": "reportUnknownMemberType", "range": { - "startColumn": 26, - "endColumn": 9, - "lineCount": 3 + "startColumn": 9, + "endColumn": 19, + "lineCount": 1 } }, { "code": "reportUnknownArgumentType", "range": { - "startColumn": 40, - "endColumn": 44, + "startColumn": 24, + "endColumn": 28, "lineCount": 1 } }, { "code": "reportUnknownArgumentType", "range": { - "startColumn": 46, - "endColumn": 51, + "startColumn": 30, + "endColumn": 35, "lineCount": 1 } }, { "code": "reportUnknownArgumentType", "range": { - "startColumn": 28, - "endColumn": 33, + "startColumn": 37, + "endColumn": 39, "lineCount": 1 } }, { "code": "reportUnknownArgumentType", "range": { - "startColumn": 42, - "endColumn": 57, + "startColumn": 21, + "endColumn": 29, "lineCount": 1 } - } - ], - "./grudge/models/advection.py": [ + }, { - "code": "reportUnknownParameterType", + "code": "reportArgumentType", + "range": { + "startColumn": 31, + "endColumn": 37, + "lineCount": 1 + } + }, + { + "code": "reportUnknownVariableType", "range": { "startColumn": 4, - "endColumn": 23, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 24, - "endColumn": 29, + "startColumn": 16, + "endColumn": 31, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 24, - "endColumn": 29, + "startColumn": 15, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 31, - "endColumn": 40, + "startColumn": 15, + "endColumn": 36, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownArgumentType", "range": { - "startColumn": 31, + "startColumn": 29, "endColumn": 40, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 42, - "endColumn": 49, + "startColumn": 15, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 42, - "endColumn": 49, + "startColumn": 15, + "endColumn": 81, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 51, - "endColumn": 59, + "startColumn": 55, + "endColumn": 66, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 51, - "endColumn": 59, + "startColumn": 69, + "endColumn": 80, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 4, - "endColumn": 8, + "startColumn": 8, + "endColumn": 16, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 11, - "endColumn": 22, + "startColumn": 19, + "endColumn": 26, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 11, - "endColumn": 36, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 4, - "endColumn": 6, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 9, - "endColumn": 19, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 4, - "endColumn": 10, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 24, - "endColumn": 28, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 30, - "endColumn": 35, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 37, - "endColumn": 39, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 21, - "endColumn": 29, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 31, - "endColumn": 37, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 4, - "endColumn": 13, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 16, - "endColumn": 31, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 15, - "endColumn": 26, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 15, - "endColumn": 36, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 29, - "endColumn": 40, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 15, - "endColumn": 26, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 15, - "endColumn": 81, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 55, - "endColumn": 66, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 69, - "endColumn": 80, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 8, - "endColumn": 16, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 19, - "endColumn": 26, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 19, - "endColumn": 32, + "startColumn": 19, + "endColumn": 32, "lineCount": 1 } }, @@ -1879,14 +1613,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownParameterType", - "range": { - "startColumn": 42, - "endColumn": 46, - "lineCount": 1 - } - }, { "code": "reportMissingParameterType", "range": { @@ -1895,14 +1621,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownParameterType", - "range": { - "startColumn": 50, - "endColumn": 56, - "lineCount": 1 - } - }, { "code": "reportMissingParameterType", "range": { @@ -1991,14 +1709,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 8, - "endColumn": 14, - "lineCount": 1 - } - }, { "code": "reportUnknownArgumentType", "range": { @@ -2032,7 +1742,7 @@ } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { "startColumn": 38, "endColumn": 44, @@ -2223,14 +1933,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 24, - "endColumn": 37, - "lineCount": 1 - } - }, { "code": "reportUnknownArgumentType", "range": { @@ -2247,14 +1949,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 14, - "endColumn": 29, - "lineCount": 1 - } - }, { "code": "reportUnknownArgumentType", "range": { @@ -2264,19 +1958,19 @@ } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownArgumentType", "range": { - "startColumn": 16, - "endColumn": 28, + "startColumn": 20, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { "startColumn": 20, - "endColumn": 25, - "lineCount": 1 + "endColumn": 33, + "lineCount": 2 } }, { @@ -2487,14 +2181,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 12, - "endColumn": 27, - "lineCount": 1 - } - }, { "code": "reportUnknownArgumentType", "range": { @@ -2511,14 +2197,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 31, - "endColumn": 49, - "lineCount": 1 - } - }, { "code": "reportArgumentType", "range": { @@ -2544,19 +2222,19 @@ } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownArgumentType", "range": { - "startColumn": 18, - "endColumn": 30, + "startColumn": 20, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { "startColumn": 20, - "endColumn": 25, - "lineCount": 1 + "endColumn": 33, + "lineCount": 2 } }, { @@ -3223,14 +2901,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 12, - "endColumn": 27, - "lineCount": 1 - } - }, { "code": "reportUnknownArgumentType", "range": { @@ -3256,19 +2926,11 @@ } }, { - "code": "reportUnknownMemberType", + "code": "reportArgumentType", "range": { "startColumn": 20, - "endColumn": 38, - "lineCount": 1 - } - }, - { - "code": "reportArgumentType", - "range": { - "startColumn": 20, - "endColumn": 53, - "lineCount": 2 + "endColumn": 53, + "lineCount": 2 } }, { @@ -3304,19 +2966,19 @@ } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownArgumentType", "range": { - "startColumn": 18, - "endColumn": 30, + "startColumn": 20, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { "startColumn": 20, - "endColumn": 25, - "lineCount": 1 + "endColumn": 33, + "lineCount": 4 } }, { @@ -3431,14 +3093,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 4, - "endColumn": 10, - "lineCount": 1 - } - }, { "code": "reportUnknownArgumentType", "range": { @@ -4223,14 +3877,6 @@ "lineCount": 1 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 12, - "endColumn": 27, - "lineCount": 1 - } - }, { "code": "reportUnknownArgumentType", "range": { @@ -4255,14 +3901,6 @@ "lineCount": 9 } }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 20, - "endColumn": 38, - "lineCount": 1 - } - }, { "code": "reportArgumentType", "range": { @@ -4304,19 +3942,19 @@ } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownArgumentType", "range": { - "startColumn": 18, - "endColumn": 30, + "startColumn": 20, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { "startColumn": 20, - "endColumn": 25, - "lineCount": 1 + "endColumn": 76, + "lineCount": 3 } }, { @@ -4362,6003 +4000,465 @@ ], "./grudge/models/em.py": [ { - "code": "reportUnknownParameterType", + "code": "reportReturnType", "range": { - "startColumn": 23, - "endColumn": 28, + "startColumn": 19, + "endColumn": 20, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportOperatorIssue", "range": { - "startColumn": 23, + "startColumn": 15, + "endColumn": 9, + "lineCount": 12 + } + }, + { + "code": "reportOperatorIssue", + "range": { + "startColumn": 15, "endColumn": 28, - "lineCount": 1 + "lineCount": 12 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 30, - "endColumn": 31, - "lineCount": 1 + "startColumn": 15, + "endColumn": 28, + "lineCount": 12 } }, { - "code": "reportMissingParameterType", + "code": "reportArgumentType", "range": { - "startColumn": 30, - "endColumn": 31, - "lineCount": 1 + "startColumn": 20, + "endColumn": 54, + "lineCount": 3 } }, { - "code": "reportUnannotatedClassAttribute", + "code": "reportUnknownVariableType", "range": { - "startColumn": 13, - "endColumn": 18, + "startColumn": 8, + "endColumn": 9, "lineCount": 1 } }, { - "code": "reportUnannotatedClassAttribute", + "code": "reportUnknownVariableType", "range": { - "startColumn": 13, - "endColumn": 14, + "startColumn": 11, + "endColumn": 12, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportCallIssue", "range": { - "startColumn": 22, - "endColumn": 27, + "startColumn": 15, + "endColumn": 23, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportArgumentType", "range": { - "startColumn": 22, - "endColumn": 27, + "startColumn": 15, + "endColumn": 23, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportCallIssue", "range": { - "startColumn": 15, - "endColumn": 28, + "startColumn": 25, + "endColumn": 33, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { - "startColumn": 29, - "endColumn": 39, + "startColumn": 25, + "endColumn": 33, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 41, - "endColumn": 47, + "startColumn": 15, + "endColumn": 19, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 49, - "endColumn": 54, + "startColumn": 19, + "endColumn": 50, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportCallIssue", "range": { - "startColumn": 12, - "endColumn": 13, + "startColumn": 21, + "endColumn": 50, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportArgumentType", "range": { - "startColumn": 12, - "endColumn": 13, + "startColumn": 29, + "endColumn": 49, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { - "startColumn": 19, - "endColumn": 20, + "startColumn": 32, + "endColumn": 72, + "lineCount": 1 + } + } + ], + "./grudge/models/euler.py": [ + { + "code": "reportUnannotatedClassAttribute", + "range": { + "startColumn": 4, + "endColumn": 19, "lineCount": 1 } }, { "code": "reportUnknownParameterType", "range": { - "startColumn": 34, - "endColumn": 41, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { "code": "reportMissingParameterType", "range": { - "startColumn": 34, - "endColumn": 41, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { "code": "reportMissingParameterType", "range": { - "startColumn": 43, - "endColumn": 47, + "startColumn": 15, + "endColumn": 16, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportMissingParameterType", "range": { - "startColumn": 8, - "endColumn": 14, + "startColumn": 20, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportMissingParameterType", "range": { - "startColumn": 12, - "endColumn": 17, + "startColumn": 30, + "endColumn": 41, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportMissingParameterType", "range": { - "startColumn": 16, - "endColumn": 29, + "startColumn": 47, + "endColumn": 54, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportMissingParameterType", "range": { - "startColumn": 27, - "endColumn": 33, + "startColumn": 58, + "endColumn": 63, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 27, - "endColumn": 33, + "startColumn": 4, + "endColumn": 5, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 29, - "endColumn": 42, + "startColumn": 7, + "endColumn": 8, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 56, - "endColumn": 62, + "startColumn": 4, + "endColumn": 8, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 28, - "endColumn": 49, + "startColumn": 11, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 16, - "endColumn": 30, + "startColumn": 4, + "endColumn": 8, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 16, - "endColumn": 37, + "startColumn": 4, + "endColumn": 11, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 16, - "endColumn": 35, + "startColumn": 14, + "endColumn": 21, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 16, - "endColumn": 42, + "startColumn": 14, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 8, - "endColumn": 16, + "startColumn": 4, + "endColumn": 5, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 23, - "endColumn": 24, - "lineCount": 1 - } - }, - { - "code": "reportMissingParameterType", - "range": { - "startColumn": 23, - "endColumn": 24, - "lineCount": 1 - } - }, - { - "code": "reportUnknownParameterType", - "range": { - "startColumn": 26, - "endColumn": 27, - "lineCount": 1 - } - }, - { - "code": "reportMissingParameterType", - "range": { - "startColumn": 26, - "endColumn": 27, - "lineCount": 1 - } - }, - { - "code": "reportUnknownParameterType", - "range": { - "startColumn": 29, - "endColumn": 39, - "lineCount": 1 - } - }, - { - "code": "reportMissingParameterType", - "range": { - "startColumn": 29, - "endColumn": 39, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 19, - "endColumn": 69, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 35, - "endColumn": 68, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 48, - "endColumn": 49, - "lineCount": 1 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 53, - "endColumn": 67, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 26, - "endColumn": 73, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 57, - 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"code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 43, - "endColumn": 53, - "lineCount": 1 + "startColumn": 15, + "endColumn": 9, + "lineCount": 5 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { "startColumn": 55, "endColumn": 60, @@ -10366,852 +4466,812 @@ } }, { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 12, - "endColumn": 71, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 35, - "endColumn": 45, + "startColumn": 21, + "endColumn": 42, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportOptionalCall", "range": { - "startColumn": 47, - "endColumn": 52, + "startColumn": 21, + "endColumn": 78, "lineCount": 1 } }, { "code": "reportUnknownParameterType", "range": { - "startColumn": 17, + "startColumn": 8, "endColumn": 22, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportIncompatibleMethodOverride", "range": { - 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"startColumn": 20, - "endColumn": 21, - "lineCount": 5 + "startColumn": 55, + "endColumn": 59, + "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 36, - "endColumn": 41, + "startColumn": 22, + "endColumn": 27, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 12, - "endColumn": 23, + "startColumn": 11, + "endColumn": 31, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 12, - "endColumn": 24, + "startColumn": 20, + "endColumn": 40, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 12, - "endColumn": 24, + "startColumn": 20, + "endColumn": 61, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 12, - "endColumn": 23, + "startColumn": 22, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 12, - "endColumn": 23, + "startColumn": 30, + "endColumn": 50, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportOperatorIssue", "range": { - "startColumn": 20, - "endColumn": 25, + "startColumn": 12, + "endColumn": 69, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { - "startColumn": 20, - "endColumn": 21, - "lineCount": 5 + "startColumn": 52, + "endColumn": 68, + "lineCount": 1 } - }, + } + ], + "./grudge/models/wave.py": [ { - "code": "reportUnknownVariableType", + "code": "reportAssignmentType", "range": { - "startColumn": 36, - "endColumn": 41, + "startColumn": 39, + "endColumn": 47, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportAssignmentType", "range": { - "startColumn": 12, - "endColumn": 23, + "startColumn": 37, + "endColumn": 46, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportAssignmentType", "range": { - 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"startColumn": 22, - "endColumn": 38, + "startColumn": 15, + "endColumn": 20, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 4, - "endColumn": 9, + "startColumn": 15, + "endColumn": 34, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 12, - "endColumn": 31, + "startColumn": 46, + "endColumn": 55, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 4, - "endColumn": 8, + "startColumn": 23, + "endColumn": 28, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportArgumentType", "range": { - "startColumn": 11, - "endColumn": 28, + "startColumn": 30, + "endColumn": 36, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 60, - "endColumn": 64, + "startColumn": 16, + "endColumn": 21, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 66, - "endColumn": 71, + "startColumn": 25, + "endColumn": 30, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 37, - "endColumn": 73, + "startColumn": 31, + "endColumn": 36, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { - "startColumn": 37, - "endColumn": 73, + "startColumn": 41, + "endColumn": 47, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 28, - "endColumn": 32, + "startColumn": 49, + "endColumn": 54, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 34, - "endColumn": 39, + "startColumn": 55, + "endColumn": 60, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 41, - "endColumn": 46, + "startColumn": 23, + "endColumn": 24, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 61, - "endColumn": 64, + "startColumn": 23, + "endColumn": 24, "lineCount": 1 } }, { "code": "reportUnknownParameterType", "range": { - "startColumn": 9, - "endColumn": 13, + "startColumn": 26, + "endColumn": 27, "lineCount": 1 } }, { "code": "reportMissingParameterType", "range": { - "startColumn": 9, - "endColumn": 13, - "lineCount": 1 - } - }, - { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 26, + "endColumn": 27, "lineCount": 1 } }, @@ -11219,15 +5279,15 @@ "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 11, + "endColumn": 9, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 13, - "endColumn": 17, + "startColumn": 8, + "endColumn": 9, "lineCount": 1 } }, @@ -11235,55 +5295,55 @@ "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 13, + "endColumn": 12, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { "startColumn": 15, - "endColumn": 18, + "endColumn": 30, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 11, - "endColumn": 56, - "lineCount": 4 + "startColumn": 8, + "endColumn": 13, + "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 11, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 57, - "endColumn": 61, + "startColumn": 12, + "endColumn": 18, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 57, - "endColumn": 61, + "startColumn": 12, + "endColumn": 18, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, @@ -11291,263 +5351,247 @@ "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 11, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 13, - "endColumn": 17, + "startColumn": 8, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportArgumentType", "range": { - "startColumn": 8, - "endColumn": 10, + "startColumn": 48, + "endColumn": 66, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 12, - "endColumn": 15, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 15, - "endColumn": 81, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 77, - "endColumn": 80, + "startColumn": 8, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportArgumentType", "range": { - "startColumn": 48, + "startColumn": 42, "endColumn": 52, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportArgumentType", "range": { - "startColumn": 48, - "endColumn": 52, + "startColumn": 35, + "endColumn": 45, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 17, + "endColumn": 22, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportMissingParameterType", "range": { - "startColumn": 8, - "endColumn": 12, + "startColumn": 17, + "endColumn": 22, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 13, - "endColumn": 17, + "startColumn": 37, + "endColumn": 45, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 8, - "endColumn": 10, + "startColumn": 60, + "endColumn": 69, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportOperatorIssue", "range": { - "startColumn": 12, - "endColumn": 16, + "startColumn": 20, + "endColumn": 55, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportOperatorIssue", "range": { - "startColumn": 11, - "endColumn": 34, - "lineCount": 4 + "startColumn": 20, + "endColumn": 56, + "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 46, - "endColumn": 48, + "startColumn": 40, + "endColumn": 45, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportIndexIssue", "range": { "startColumn": 8, - "endColumn": 12, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportIndexIssue", "range": { "startColumn": 8, - "endColumn": 61, - "lineCount": 2 + "endColumn": 14, + "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportIndexIssue", "range": { - "startColumn": 15, - "endColumn": 22, + "startColumn": 8, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportIndexIssue", "range": { - "startColumn": 24, - "endColumn": 30, + "startColumn": 20, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportOperatorIssue", "range": { - "startColumn": 32, + "startColumn": 20, "endColumn": 61, - "lineCount": 2 - } - }, - { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 33, - "endColumn": 59, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 33, - "endColumn": 58, + "startColumn": 32, + "endColumn": 36, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 28, - "endColumn": 71, + "startColumn": 32, + "endColumn": 36, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportIncompatibleMethodOverride", "range": { - "startColumn": 29, + "startColumn": 8, "endColumn": 35, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", - "range": { - "startColumn": 38, - "endColumn": 44, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", + "code": "reportImplicitOverride", "range": { "startColumn": 8, - "endColumn": 18, + "endColumn": 35, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 21, - "endColumn": 42, + "startColumn": 42, + "endColumn": 46, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 20, - "endColumn": 30, + "startColumn": 42, + "endColumn": 46, "lineCount": 1 } }, { "code": "reportUnknownParameterType", "range": { - "startColumn": 22, - "endColumn": 27, + "startColumn": 48, + "endColumn": 49, "lineCount": 1 } }, { "code": "reportMissingParameterType", "range": { - "startColumn": 22, - "endColumn": 27, + "startColumn": 48, + "endColumn": 49, "lineCount": 1 } }, { "code": "reportUnknownParameterType", "range": { - "startColumn": 29, - "endColumn": 34, + "startColumn": 56, + "endColumn": 62, "lineCount": 1 } }, { "code": "reportMissingParameterType", "range": { - "startColumn": 29, - "endColumn": 34, + "startColumn": 56, + "endColumn": 62, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportImplicitOverride", "range": { - "startColumn": 36, - "endColumn": 39, + "startColumn": 8, + "endColumn": 29, "lineCount": 1 } }, @@ -11555,167 +5599,159 @@ "code": "reportMissingParameterType", "range": { "startColumn": 36, - "endColumn": 39, - "lineCount": 1 - } - }, - { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 4, - "endColumn": 12, + "endColumn": 40, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportMissingParameterType", "range": { - "startColumn": 15, - "endColumn": 34, + "startColumn": 42, + "endColumn": 47, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportMissingParameterType", "range": { - "startColumn": 4, - "endColumn": 13, + "startColumn": 51, + "endColumn": 57, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 16, - "endColumn": 35, + "startColumn": 23, + "endColumn": 28, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportMissingParameterType", "range": { - "startColumn": 4, - "endColumn": 8, + "startColumn": 23, + "endColumn": 28, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 11, - "endColumn": 28, + "startColumn": 30, + "endColumn": 31, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 60, - "endColumn": 64, + "startColumn": 30, + "endColumn": 31, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 66, - "endColumn": 71, + "startColumn": 33, + "endColumn": 41, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportMissingParameterType", "range": { - "startColumn": 37, - "endColumn": 73, + "startColumn": 33, + "endColumn": 41, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 37, - "endColumn": 73, + "startColumn": 12, + "endColumn": 21, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 28, - "endColumn": 32, + "startColumn": 12, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 34, - "endColumn": 43, + "startColumn": 12, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 45, - "endColumn": 53, + "startColumn": 12, + "endColumn": 23, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 70, - "endColumn": 73, + "startColumn": 12, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 42, - "endColumn": 46, + "startColumn": 12, + "endColumn": 20, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownLambdaType", "range": { - "startColumn": 42, - "endColumn": 46, + "startColumn": 30, + "endColumn": 34, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownLambdaType", "range": { - "startColumn": 48, - "endColumn": 54, + "startColumn": 36, + "endColumn": 41, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownLambdaType", "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 43, + "endColumn": 44, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 8, - "endColumn": 12, + "startColumn": 46, + "endColumn": 57, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownLambdaType", "range": { - "startColumn": 13, - "endColumn": 17, + "startColumn": 46, + "endColumn": 63, "lineCount": 1 } }, @@ -11723,447 +5759,439 @@ "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 13, + "endColumn": 12, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { "startColumn": 15, - "endColumn": 19, + "endColumn": 32, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnannotatedClassAttribute", "range": { - "startColumn": 11, - "endColumn": 56, - "lineCount": 4 + "startColumn": 13, + "endColumn": 18, + "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnannotatedClassAttribute", "range": { - "startColumn": 8, - "endColumn": 12, + "startColumn": 13, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 54, - "endColumn": 58, + "startColumn": 8, + "endColumn": 21, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnannotatedClassAttribute", "range": { - "startColumn": 54, - "endColumn": 58, + "startColumn": 13, + "endColumn": 21, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 8, + "endColumn": 12, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 8, - "endColumn": 16, + "startColumn": 15, + "endColumn": 26, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 18, - "endColumn": 21, + "startColumn": 8, + "endColumn": 16, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 13, - "endColumn": 17, + "startColumn": 19, + "endColumn": 28, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { "startColumn": 8, - "endColumn": 13, + "endColumn": 17, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnannotatedClassAttribute", "range": { - "startColumn": 15, - "endColumn": 23, + "startColumn": 13, + "endColumn": 17, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 25, - "endColumn": 28, + "startColumn": 20, + "endColumn": 31, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 15, - "endColumn": 9, - "lineCount": 4 + "startColumn": 16, + "endColumn": 23, + "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 12, - "endColumn": 15, + "startColumn": 16, + "endColumn": 29, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 29, + "startColumn": 30, "endColumn": 37, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 53, - "endColumn": 57, + "startColumn": 30, + "endColumn": 45, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnannotatedClassAttribute", "range": { - "startColumn": 53, - "endColumn": 57, + "startColumn": 13, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnannotatedClassAttribute", "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 13, + "endColumn": 24, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnannotatedClassAttribute", "range": { - "startColumn": 8, - "endColumn": 12, + "startColumn": 13, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnannotatedClassAttribute", "range": { "startColumn": 13, - "endColumn": 17, + "endColumn": 27, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnannotatedClassAttribute", "range": { - "startColumn": 8, - "endColumn": 13, + "startColumn": 13, + "endColumn": 22, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 15, - "endColumn": 19, + "startColumn": 19, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", - "range": { - "startColumn": 11, - "endColumn": 34, - "lineCount": 4 - } - }, - { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 44, - "endColumn": 49, + "startColumn": 19, + "endColumn": 25, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 12, + "endColumn": 9, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 46, - "endColumn": 63, + "startColumn": 8, + "endColumn": 9, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 46, - "endColumn": 63, + "startColumn": 8, + "endColumn": 9, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 65, - "endColumn": 81, + "startColumn": 8, + "endColumn": 12, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 65, - "endColumn": 81, + "startColumn": 15, + "endColumn": 20, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 14, - "endColumn": 35, + "startColumn": 15, + "endColumn": 34, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 14, - "endColumn": 35, + "startColumn": 46, + "endColumn": 55, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 8, - "endColumn": 61, - "lineCount": 2 + "startColumn": 19, + "endColumn": 24, + "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 15, - "endColumn": 22, + "startColumn": 25, + "endColumn": 30, "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 24, - "endColumn": 30, + "startColumn": 33, + "endColumn": 38, "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 32, - "endColumn": 61, - "lineCount": 2 + "startColumn": 39, + "endColumn": 44, + "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportArgumentType", "range": { - "startColumn": 33, - "endColumn": 59, + "startColumn": 46, + "endColumn": 52, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 33, - "endColumn": 58, + "startColumn": 13, + "endColumn": 18, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 25, - "endColumn": 32, + "startColumn": 21, + "endColumn": 26, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 25, - "endColumn": 32, + "startColumn": 29, + "endColumn": 34, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 34, + "startColumn": 35, "endColumn": 40, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 34, - "endColumn": 40, + "startColumn": 20, + "endColumn": 25, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 35, - "endColumn": 52, + "startColumn": 26, + "endColumn": 31, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 35, - "endColumn": 54, + "startColumn": 34, + "endColumn": 39, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 56, - "endColumn": 74, + "startColumn": 42, + "endColumn": 47, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { - "startColumn": 56, - "endColumn": 74, + "startColumn": 37, + "endColumn": 43, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 8, - "endColumn": 13, + "startColumn": 45, + "endColumn": 50, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 16, - "endColumn": 33, + "startColumn": 53, + "endColumn": 58, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 27, - "endColumn": 42, + "startColumn": 61, + "endColumn": 66, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 27, - "endColumn": 42, + "startColumn": 69, + "endColumn": 74, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 44, - "endColumn": 62, + "startColumn": 23, + "endColumn": 24, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 44, - "endColumn": 62, + "startColumn": 23, + "endColumn": 24, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 29, - "endColumn": 44, + "startColumn": 26, + "endColumn": 27, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 29, - "endColumn": 44, + "startColumn": 26, + "endColumn": 27, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 46, - "endColumn": 63, + "startColumn": 8, + "endColumn": 9, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 46, - "endColumn": 63, + "startColumn": 8, + "endColumn": 9, "lineCount": 1 } }, @@ -12171,15 +6199,15 @@ "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 18, + "endColumn": 12, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 21, - "endColumn": 42, + "startColumn": 15, + "endColumn": 30, "lineCount": 1 } }, @@ -12187,79 +6215,79 @@ "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 15, + "endColumn": 9, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 18, - "endColumn": 40, + "startColumn": 12, + "endColumn": 21, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 18, - "endColumn": 50, + "startColumn": 8, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 53, - "endColumn": 60, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 62, - "endColumn": 72, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 28, - "endColumn": 45, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 47, - "endColumn": 63, + "startColumn": 12, + "endColumn": 18, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 43, - "endColumn": 47, + "startColumn": 12, + "endColumn": 18, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 43, - "endColumn": 47, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, @@ -12267,351 +6295,353 @@ "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 11, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 13, - "endColumn": 17, + "startColumn": 8, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportArgumentType", "range": { - "startColumn": 8, - "endColumn": 13, + "startColumn": 48, + "endColumn": 66, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 15, - "endColumn": 18, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 4, - "endColumn": 10, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 13, - "endColumn": 33, + "startColumn": 8, + "endColumn": 13, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 11, - "endColumn": 58, + "startColumn": 8, + "endColumn": 16, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 54, - "endColumn": 57, + "startColumn": 64, + "endColumn": 73, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 54, - "endColumn": 67, + "startColumn": 74, + "endColumn": 83, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 54, - "endColumn": 67, + "startColumn": 8, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { - "startColumn": 14, - "endColumn": 43, + "startColumn": 43, + "endColumn": 53, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { - "startColumn": 14, - "endColumn": 43, + "startColumn": 35, + "endColumn": 45, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 8, - "endColumn": 44, + "startColumn": 17, + "endColumn": 22, "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportMissingParameterType", "range": { - "startColumn": 15, - "endColumn": 18, + "startColumn": 17, + "endColumn": 22, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 20, - "endColumn": 42, + "startColumn": 37, + "endColumn": 45, "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 20, - "endColumn": 44, + "startColumn": 60, + "endColumn": 69, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 29, - "endColumn": 32, + "startColumn": 28, + "endColumn": 33, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportIndexIssue", "range": { - "startColumn": 29, - "endColumn": 32, + "startColumn": 8, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportIndexIssue", "range": { "startColumn": 8, - "endColumn": 13, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownMemberType", + "code": "reportIndexIssue", "range": { - "startColumn": 16, - "endColumn": 29, + "startColumn": 8, + "endColumn": 14, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportIndexIssue", "range": { - "startColumn": 44, - "endColumn": 49, + "startColumn": 20, + "endColumn": 26, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 51, - "endColumn": 65, + "startColumn": 32, + "endColumn": 45, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownParameterType", "range": { - "startColumn": 51, - "endColumn": 65, + "startColumn": 32, + "endColumn": 36, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { "startColumn": 32, - "endColumn": 45, + "endColumn": 36, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportImplicitOverride", "range": { - "startColumn": 51, - "endColumn": 55, + "startColumn": 8, + "endColumn": 35, "lineCount": 1 } }, { "code": "reportMissingParameterType", "range": { - "startColumn": 51, - "endColumn": 55, + "startColumn": 42, + "endColumn": 46, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportMissingParameterType", "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 50, + "endColumn": 56, "lineCount": 1 } - }, + } + ], + "./grudge/op.py": [ { "code": "reportUnknownVariableType", "range": { - "startColumn": 8, - "endColumn": 11, + "startColumn": 33, + "endColumn": 39, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 13, - "endColumn": 17, + "startColumn": 4, + "endColumn": 24, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 8, - "endColumn": 10, + "startColumn": 4, + "endColumn": 19, "lineCount": 1 } }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 12, - "endColumn": 15, + "startColumn": 4, + "endColumn": 19, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 55, - "endColumn": 58, + "startColumn": 4, + "endColumn": 19, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportCallIssue", "range": { - "startColumn": 14, - "endColumn": 35, + "startColumn": 15, + "endColumn": 81, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", - "range": { - "startColumn": 8, - "endColumn": 64, - "lineCount": 2 - } - }, - { - "code": "reportUnknownLambdaType", + "code": "reportUnknownVariableType", "range": { "startColumn": 15, - "endColumn": 23, + "endColumn": 81, "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportArgumentType", "range": { - "startColumn": 25, - "endColumn": 32, + "startColumn": 35, + "endColumn": 75, "lineCount": 1 } }, { - "code": "reportUnknownLambdaType", + "code": "reportUnknownArgumentType", "range": { - "startColumn": 34, - "endColumn": 64, - "lineCount": 2 + "startColumn": 28, + "endColumn": 71, + "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 35, - "endColumn": 62, + "startColumn": 29, + "endColumn": 35, "lineCount": 1 } }, { "code": "reportUnknownMemberType", "range": { - "startColumn": 35, - "endColumn": 61, + "startColumn": 38, + "endColumn": 44, "lineCount": 1 } }, { - "code": "reportUnknownParameterType", + "code": "reportUnknownVariableType", "range": { - "startColumn": 48, - "endColumn": 52, + "startColumn": 8, + "endColumn": 18, "lineCount": 1 } }, { - "code": "reportMissingParameterType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 48, - "endColumn": 52, + "startColumn": 21, + "endColumn": 42, "lineCount": 1 } }, { "code": "reportUnknownArgumentType", "range": { - "startColumn": 11, - "endColumn": 15, + "startColumn": 20, + "endColumn": 30, "lineCount": 1 } }, + { + "code": "reportCallIssue", + "range": { + "startColumn": 15, + "endColumn": 9, + "lineCount": 4 + } + }, { "code": "reportUnknownVariableType", "range": { - "startColumn": 8, - "endColumn": 11, - "lineCount": 1 + "startColumn": 15, + "endColumn": 9, + "lineCount": 4 } }, { - "code": "reportUnknownArgumentType", + "code": "reportArgumentType", "range": { - "startColumn": 13, - "endColumn": 17, + "startColumn": 12, + "endColumn": 60, "lineCount": 1 } }, @@ -12619,31 +6649,47 @@ "code": "reportUnknownVariableType", "range": { "startColumn": 8, - "endColumn": 13, + "endColumn": 18, "lineCount": 1 } }, { - "code": "reportUnknownVariableType", + "code": "reportUnknownMemberType", "range": { - "startColumn": 15, - "endColumn": 18, + "startColumn": 21, + "endColumn": 42, "lineCount": 1 } }, { "code": "reportUnknownArgumentType", "range": { - "startColumn": 44, - "endColumn": 49, + "startColumn": 62, + "endColumn": 72, "lineCount": 1 } }, { - "code": "reportUnknownArgumentType", + "code": "reportCallIssue", "range": { - "startColumn": 51, - "endColumn": 54, + "startColumn": 15, + "endColumn": 9, + "lineCount": 3 + } + }, + { + "code": "reportUnknownVariableType", + "range": { + "startColumn": 15, + "endColumn": 9, + "lineCount": 3 + } + }, + { + "code": "reportArgumentType", + "range": { + "startColumn": 12, + "endColumn": 60, "lineCount": 1 } } @@ -14271,14 +8317,6 @@ } ], "./grudge/trace_pair.py": [ - { - "code": "reportPrivateLocalImportUsage", - "range": { - "startColumn": 4, - "endColumn": 23, - "lineCount": 1 - } - }, { "code": "reportUnknownParameterType", "range": { diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 1dc69d12..3551012b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -31,7 +31,7 @@ jobs: curl -L -O https://tiker.net/ci-support-v0 . ./ci-support-v0 build_py_project_in_conda_env - cipip install pytest modepy + cipip install pytest modepy optype cipip install basedpyright basedpyright diff --git a/doc/conf.py b/doc/conf.py index cca6d818..9672c9f0 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -40,8 +40,8 @@ sphinxconfig_missing_reference_aliases = { # numpy - "np.floating": "class:numpy.floating", "DTypeLike": "obj:numpy.typing.DTypeLike", + "np.floating": "class:numpy.floating", # mpi4py "Intracomm": "mpi4py.MPI.Intracomm", @@ -54,26 +54,26 @@ "cl_array.Allocator": "class:pyopencl.array.Allocator", # actx - "arraycontext.typing.ArithArrayContainerT": - "obj:arraycontext.ArithArrayContainerT", - "ScalarLike": "obj:arraycontext.ScalarLike", - "Array": "obj:arraycontext.Array", - "ArrayContainer": "obj:arraycontext.ArrayContainer", "ArithArrayContainer": "obj:arraycontext.ArithArrayContainer", "ArithArrayContainerT": "obj:arraycontext.ArithArrayContainerT", - "ArrayOrContainer": "obj:arraycontext.ArrayOrContainer", + "Array": "obj:arraycontext.Array", + "ArrayContainer": "obj:arraycontext.ArrayContainer", "ArrayOrArithContainer": "obj:arraycontext.ArrayOrArithContainer", + "ArrayOrContainer": "obj:arraycontext.ArrayOrContainer", + "ArrayOrContainerOrScalar": "obj:arraycontext.ArrayOrContainerOrScalar", "ArrayOrContainerOrScalarT": "obj:arraycontext.ArrayOrContainerOrScalarT", + "ScalarLike": "obj:arraycontext.ScalarLike", + "arraycontext.typing.ArithArrayContainerT": "obj:arraycontext.ArithArrayContainerT", # meshmode "DOFArray": "meshmode.dof_array.DOFArray", - "Mesh": "meshmode.mesh.Mesh", "Discretization": "class:meshmode.discretization.Discretization", + "Mesh": "meshmode.mesh.Mesh", # grudge "DiscretizationTag": "obj:grudge.dof_desc.DiscretizationTag", - "VolumeTag": "obj:grudge.dof_desc.VolumeTag", "TracePair": "class:grudge.trace_pair.TracePair", + "VolumeTag": "obj:grudge.dof_desc.VolumeTag", } diff --git a/grudge/geometry/metrics.py b/grudge/geometry/metrics.py index 15e73e6b..14086596 100644 --- a/grudge/geometry/metrics.py +++ b/grudge/geometry/metrics.py @@ -60,8 +60,8 @@ """ -from functools import reduce -from operator import add +from functools import partial, reduce +from operator import add, xor from typing import TYPE_CHECKING import numpy as np @@ -75,8 +75,8 @@ DiscretizationAmbientDimAxisTag, DiscretizationTopologicalDimAxisTag, ) -from pymbolic.geometric_algebra import MultiVector -from pytools import memoize_in +from pymbolic.geometric_algebra import MultiVector, get_euclidean_space +from pytools import flatten, memoize_in, product import grudge.dof_desc as dof_desc from grudge import DiscretizationCollection @@ -96,9 +96,9 @@ def _geometry_to_quad_if_requested( dd: DOFDesc, vec: DOFArray, _use_geoderiv_connection: bool - ): + ) -> DOFArray: - def to_quad(vec: DOFArray): + def to_quad(vec: DOFArray) -> DOFArray: if not dd.uses_quadrature(): return vec return dcoll.connection_from_dds(inner_dd, dd)(vec) @@ -172,15 +172,15 @@ def forward_metric_nth_derivative( ref_axes = ((ref_axes, 1),) if not isinstance(ref_axes, tuple): - raise ValueError("ref_axes must be a tuple") + raise ValueError(f"'ref_axes' must be a tuple: {type(ref_axes)}") if tuple(sorted(ref_axes)) != ref_axes: - raise ValueError("ref_axes must be sorted") + raise ValueError(f"'ref_axes' must be sorted: {ref_axes}") if len(set(ref_axes)) != len(ref_axes): - raise ValueError("ref_axes must not contain an axis more than once") + raise ValueError( + f"'ref_axes' must not contain an axis more than once: {ref_axes}") - from pytools import flatten flat_ref_axes = flatten([rst_axis] * n for rst_axis, n in ref_axes) from meshmode.discretization import num_reference_derivative @@ -453,11 +453,9 @@ def inverse_metric_derivative( for rst in range(dim)] # Yay Cramer's rule! - from functools import partial, reduce - from operator import xor as outerprod_op - outerprod = partial(reduce, outerprod_op) + outerprod = partial(reduce, xor) - def outprod_with_unit(i: int, at: int): + def outprod_with_unit(i: int, at: int) -> MultiVector[DOFArray]: unit_vec = np.zeros(dim) unit_vec[i] = 1 @@ -532,7 +530,7 @@ def inverse_surface_metric_derivative_mat( dd: ToDOFDescConvertible = None, *, times_area_element: bool = False, _use_geoderiv_connection: bool = False - ): + ) -> DOFArray: r"""Computes the matrix of inverse surface metric derivatives, indexed by ``(xyz_axis, rst_axis)``. It returns all values of :func:`inverse_surface_metric_derivative_mat` in cached matrix form. @@ -557,7 +555,7 @@ def inverse_surface_metric_derivative_mat( @memoize_in(dcoll, (inverse_surface_metric_derivative_mat, dd, times_area_element, _use_geoderiv_connection)) - def _inv_surf_metric_deriv(): + def _inv_surf_metric_deriv() -> DOFArray: if times_area_element: multiplier = area_element(actx, dcoll, dd=dd, _use_geoderiv_connection=_use_geoderiv_connection) @@ -600,7 +598,7 @@ def _signed_face_ones( discr = dcoll.discr_from_dd(dd.with_discr_tag(DISCR_TAG_BASE)) - new_group_arrays = [] + new_group_arrays: list[np.ndarray[tuple[int, int], np.dtype[np.floating]]] = [] for dgrp, grp in zip(discr.groups, all_faces_conn.groups, strict=True): sign = np.ones((dgrp.nelements, dgrp.nunit_dofs), @@ -613,7 +611,6 @@ def _signed_face_ones( new_group_arrays.append(sign) - from meshmode.dof_array import DOFArray return actx.from_numpy(DOFArray(actx, tuple(new_group_arrays))) @@ -638,15 +635,11 @@ def parametrization_derivative( dim = dcoll.discr_from_dd(dd).dim if dim == 0: - from pymbolic.geometric_algebra import get_euclidean_space - return MultiVector( _signed_face_ones(actx, dcoll, dd), space=get_euclidean_space(dcoll.ambient_dim) ) - from pytools import product - res = product( forward_metric_derivative_mv( actx, dcoll, rst_axis, dd, @@ -655,6 +648,7 @@ def parametrization_derivative( ) if isinstance(res, int): return MultiVector(res) + return res @@ -703,11 +697,12 @@ def area_element( dd = DD_VOLUME_ALL @memoize_in(dcoll, (area_element, dd, _use_geoderiv_connection)) - def _area_elements(): + def _area_elements() -> DOFArray: result = actx.np.sqrt( pseudoscalar( actx, dcoll, dd=dd, _use_geoderiv_connection=_use_geoderiv_connection).norm_squared()) + assert isinstance(result, DOFArray) return actx.freeze( actx.tag(NameHint(f"area_el_{dd.as_identifier()}"), result)) @@ -783,7 +778,7 @@ def mv_normal( use_geoderiv_connection = actx.supports_nonscalar_broadcasting @memoize_in(dcoll, (mv_normal, dd, use_geoderiv_connection)) - def _normal(): + def _normal() -> MultiVector[DOFArray]: dim = dcoll.discr_from_dd(dd).dim ambient_dim = dcoll.ambient_dim @@ -834,8 +829,11 @@ def _normal(): return actx.thaw(_normal()) -def normal(actx: ArrayContext, dcoll: DiscretizationCollection, dd: DOFDesc, - *, _use_geoderiv_connection: bool | None = None): +def normal(actx: ArrayContext, + dcoll: DiscretizationCollection, + dd: DOFDesc, + *, _use_geoderiv_connection: bool | None = None, + ) -> obj_array.ObjectArray1D[DOFArray]: """Get the unit normal to the specified surface discretization, *dd*. This supports both volume discretizations (where ambient == topological dimension) and surface discretizations @@ -897,8 +895,6 @@ def second_fundamental_form( else: raise ValueError(f"{dim}D surfaces not supported") - from pytools import flatten - form2 = np.empty((dim, dim), dtype=object) for ref_axes in second_ref_axes: diff --git a/grudge/models/__init__.py b/grudge/models/__init__.py index c101208e..508553e8 100644 --- a/grudge/models/__init__.py +++ b/grudge/models/__init__.py @@ -28,6 +28,13 @@ """ from abc import ABC, abstractmethod +from typing import TYPE_CHECKING, Any + + +if TYPE_CHECKING: + from arraycontext import Array, ArrayContext + + from grudge.discretization import DiscretizationCollection class Operator(ABC): # noqa: B024 @@ -40,11 +47,11 @@ class Operator(ABC): # noqa: B024 """ -class HyperbolicOperator(Operator): +class HyperbolicOperator(Operator, ABC): """A base class for hyperbolic Discontinuous Galerkin operators.""" @abstractmethod - def max_characteristic_velocity(self, actx, **kwargs): + def max_characteristic_velocity(self, actx: ArrayContext, **kwargs: Any) -> Array: r"""Return a maximum characteristic wavespeed for the operator. :arg actx: a :class:`arraycontext.ArrayContext`. @@ -56,7 +63,10 @@ def max_characteristic_velocity(self, actx, **kwargs): the operator. """ - def estimate_rk4_timestep(self, actx, dcoll, **kwargs): + def estimate_rk4_timestep( + self, + actx: ArrayContext, + dcoll: DiscretizationCollection, **kwargs: Any) -> Array: r"""Estimate the largest stable timestep for an RK4 method. :arg actx: a :class:`arraycontext.ArrayContext`. diff --git a/grudge/models/em.py b/grudge/models/em.py index 4ee05075..15ce44ec 100644 --- a/grudge/models/em.py +++ b/grudge/models/em.py @@ -34,40 +34,55 @@ """ -from typing import TYPE_CHECKING, Literal, final +from dataclasses import dataclass +from typing import TYPE_CHECKING, Any, ClassVar, Literal, TypeAlias, final, overload import numpy as np +from typing_extensions import override +import pymbolic.primitives as prim import pytools.obj_array as obj_array -from arraycontext import get_container_context_recursively -from meshmode.mesh import BTAG_ALL, BTAG_NONE +from arraycontext import ( + Array, + ArrayContext, + ArrayOrArithContainerOrScalar, + ArrayOrContainer, + get_container_context_recursively, +) +from meshmode.mesh import BTAG_ALL, BTAG_NONE, BoundaryTag, Mesh from pytools import levi_civita, memoize_method import grudge.geometry as geo import grudge.op as op +from grudge.dof_desc import as_dofdesc from grudge.models import HyperbolicOperator if TYPE_CHECKING: - from collections.abc import Sequence + from collections.abc import Callable, Iterator, Sequence from grudge.discretization import DiscretizationCollection + from grudge.trace_pair import TracePair + +Vector: TypeAlias = obj_array.ObjectArray1D[ArrayOrArithContainerOrScalar] +SubsetMask: TypeAlias = tuple[bool, bool, bool] +VectorIndex: TypeAlias = np.ndarray[tuple[int], np.dtype[np.integer]] # {{{ helpers # NOTE: Hack for getting the derivative operators to play nice # with grudge.tools.SubsettableCrossProduct +@dataclass(frozen=True) class _Dx: - def __init__(self, dcoll, i): - self.dcoll = dcoll - self.i = i + dcoll: DiscretizationCollection + i: int - def __mul__(self, other): + def __mul__(self, other: ArrayOrContainer) -> ArrayOrContainer: return op.local_d_dx(self.dcoll, self.i, other) -def is_zero(x): +def is_zero(x: object) -> bool: # DO NOT try to replace this with an attempted "== 0" comparison. # This will become an elementwise numpy operation and not do what # you want. @@ -78,12 +93,14 @@ def is_zero(x): return False -def count_subset(subset: Sequence[bool]): +def count_subset(subset: Sequence[bool]) -> int: from pytools import len_iterable return len_iterable(uc for uc in subset if uc) -def partial_to_all_subset_indices(subsets, base=0): +def partial_to_all_subset_indices( + subsets: Sequence[SubsetMask], base: int = 0 + ) -> Iterator[VectorIndex]: """Takes a sequence of bools and generates it into an array of indices to be used to insert the subset into the full set. Example: @@ -93,7 +110,7 @@ def partial_to_all_subset_indices(subsets, base=0): idx = base for subset in subsets: - result = [] + result: list[int] = [] for is_in in subset: if is_in: result.append(idx) @@ -112,21 +129,25 @@ class SubsettableCrossProduct: two operands and return an arbitrary subset of its result. """ - full_subset = (True, True, True) + full_subset: ClassVar[SubsetMask] = (True, True, True) + + op1_subset: SubsetMask + op2_subset: SubsetMask + result_subset: SubsetMask + + functions: list[Callable[[Vector, Vector], Vector]] def __init__(self, - op1_subset: tuple[bool, bool, bool] = full_subset, - op2_subset: tuple[bool, bool, bool] = full_subset, - result_subset: tuple[bool, bool, bool] = full_subset): + op1_subset: SubsetMask = full_subset, + op2_subset: SubsetMask = full_subset, + result_subset: SubsetMask = full_subset) -> None: """Construct a subset-able cross product. - :param op1_subset: The subset of indices of operand 1 to be taken into - account. Given as a 3-sequence of bools. - :param op2_subset: The subset of indices of operand 2 to be taken into - account. Given as a 3-sequence of bools. - :param result_subset: The subset of indices of the result that are - calculated. Given as a 3-sequence of bools. + + :arg op1_subset: the subset of indices of operand 1 to be taken into account. + :arg op2_subset: The subset of indices of operand 2 to be taken into account. + :arg result_subset: The subset of indices of the result that are calculated. """ - def subset_indices(subset): + def subset_indices(subset: SubsetMask) -> list[int]: return [i for i, use_component in enumerate(subset) if use_component] @@ -134,28 +155,36 @@ def subset_indices(subset): self.op2_subset = op2_subset self.result_subset = result_subset - import pymbolic - op1 = pymbolic.var("x") - op2 = pymbolic.var("y") + from pymbolic import compile + + op1 = prim.Variable("x") + op2 = prim.Variable("y") self.functions = [] - self.component_lcjk = [] + self.component_lcjk: list[list[tuple[int, int, int]]] = [] + for i, use_component in enumerate(result_subset): if use_component: this_expr = 0 - this_component = [] + this_component: list[tuple[int, int, int]] = [] for j, j_real in enumerate(subset_indices(op1_subset)): for k, k_real in enumerate(subset_indices(op2_subset)): lc = levi_civita((i, j_real, k_real)) if lc != 0: this_expr += lc*op1[j]*op2[k] this_component.append((lc, j, k)) - self.functions.append(pymbolic.compile(this_expr, - variables=[op1, op2])) + + self.functions.append(compile(this_expr, variables=[op1, op2])) self.component_lcjk.append(this_component) - def __call__(self, x, y, three_mult=None): + def __call__(self, + x: Vector, + y: Vector, + three_mult: Callable[ + [int, ArrayOrArithContainerOrScalar, ArrayOrArithContainerOrScalar], + ArrayOrArithContainerOrScalar] | None = None) -> Vector: """Compute the subsetted cross product on the indexables *x* and *y*. + :param three_mult: a function of three arguments *sign, xj, yk* used in place of the product *sign*xj*yk*. Defaults to just this product if not given. @@ -176,44 +205,73 @@ def __call__(self, x, y, three_mult=None): # {{{ MaxwellOperator class MaxwellOperator(HyperbolicOperator): - """A strong-form 3D Maxwell operator which supports fixed or variable - isotropic, non-dispersive, positive epsilon and mu. + r"""A strong-form 3D Maxwell operator which supports fixed or variable + isotropic, non-dispersive, positive :math:`\epsilon` and :math:`\mu`. - Field order is [Ex Ey Ez Hx Hy Hz]. + Field order is :math:`[E_x, E_y, E_z, H_x, H_y, H_z]`. """ - _default_dimensions = 3 + _default_dimensions: ClassVar[int] = 3 + + dcoll: DiscretizationCollection + dimensions: int + + current: ArrayOrArithContainerOrScalar + epsilon: ArrayOrArithContainerOrScalar + mu: ArrayOrArithContainerOrScalar + fixed_material: bool + + flux_type: int | float | Literal["lf"] + bdry_flux_type: int | float | Literal["lf"] + incident_bc_data: Callable[[MaxwellOperator, Vector, Vector], Vector] + + space_cross_e: SubsettableCrossProduct + space_cross_h: SubsettableCrossProduct + + pec_tag: BoundaryTag + pmc_tag: BoundaryTag + absorb_tag: BoundaryTag + incident_tag: BoundaryTag def __init__(self, dcoll: DiscretizationCollection, - epsilon: float, - mu: float, - flux_type: Literal["lf"] | float, - bdry_flux_type: Literal["lf"] | float | None = None, - pec_tag=BTAG_ALL, - pmc_tag=BTAG_NONE, - absorb_tag=BTAG_NONE, - incident_tag=BTAG_NONE, - incident_bc=lambda maxwell_op, e, h: 0, - current=0, - dimensions: int | None = None): + epsilon: ArrayOrArithContainerOrScalar, + mu: ArrayOrArithContainerOrScalar, + flux_type: int | float | Literal["lf"], + bdry_flux_type: int | float | Literal["lf"] | None = None, + pec_tag: BoundaryTag = BTAG_ALL, + pmc_tag: BoundaryTag = BTAG_NONE, + absorb_tag: BoundaryTag = BTAG_NONE, + incident_tag: BoundaryTag = BTAG_NONE, + incident_bc: Callable[[MaxwellOperator, Vector, Vector], + Vector] | None = None, + current: ArrayOrArithContainerOrScalar = 0, + dimensions: int | None = None) -> None: """ - :arg flux_type: can be in [0,1] for anything between central and upwind, - or "lf" for Lax-Friedrichs - :arg epsilon: can be a number, for fixed material throughout the - computation domain, or a TimeConstantGivenFunction for spatially - variable material coefficients - :arg mu: can be a number, for fixed material throughout the computation - domain, or a TimeConstantGivenFunction for spatially variable material - coefficients - :arg incident_bc_getter: a function of signature *(maxwell_op, e, h)* that - accepts *e* and *h* as a symbolic object arrays - returns a symbolic expression for the incident - boundary condition + :arg epsilon: can be a number, for a fixed material throughout the + computation domain or a :class:`~meshmode.dof_array.DOFArray` for + spatially variable material coefficients. + :arg mu: can be a number, for a fixed material throughout the + computation domain or a :class:`~meshmode.dof_array.DOFArray` for + spatially variable material coefficients. + + :arg flux_type: can be value in :math:`[0, 1]`, that determines a convex + combination between the central and the upwind fluxes, or ``"lf"`` + for the Lax-Friedrichs flux. + :arg bdry_flux_type: defaults to *flux_type* if not provided. + + :arg incident_bc: a function that accepts *e* and *h* as object + arrays and returns the value for the incident boundary condition. """ - self.dcoll: DiscretizationCollection = dcoll - self.dimensions: int = dimensions or self._default_dimensions + def default_incident_bc(op: MaxwellOperator, e: Vector, h: Vector) -> Vector: + return 0 + + if incident_bc is None: + incident_bc = default_incident_bc + + self.dcoll = dcoll + self.dimensions = dimensions or self._default_dimensions space_subset = (True,)*self.dimensions + (False,)*(3-self.dimensions) assert len(space_subset) == 3 @@ -232,9 +290,7 @@ def __init__(self, self.epsilon = epsilon self.mu = mu - - from pymbolic.primitives import is_constant - self.fixed_material = is_constant(epsilon) and is_constant(mu) + self.fixed_material = prim.is_constant(epsilon) and prim.is_constant(mu) self.flux_type = flux_type if bdry_flux_type is None: @@ -250,7 +306,7 @@ def __init__(self, self.current = current self.incident_bc_data = incident_bc - def flux(self, wtpair): + def flux(self, wtpair: TracePair[Vector]) -> Vector: """The numerical flux for variable coefficients. :param flux_type: can be in [0,1] for anything between central and upwind, @@ -274,6 +330,8 @@ def flux(self, wtpair): Z_ext = (mu/epsilon)**0.5 # noqa: N806 Y_ext = 1/Z_ext # noqa: N806 + from typing import cast + if self.flux_type == "lf": # if self.fixed_material: # max_c = (self.epsilon*self.mu)**(-0.5) @@ -291,26 +349,28 @@ def flux(self, wtpair): # multiplication by mu undoes material divisor below # -max_c*(mu*h.int - mu*h.ext) )) - elif isinstance(self.flux_type, int | float): + elif isinstance(self.flux_type, (int, float)): # see doc/maxima/maxwell.mac return obj_array.flat( # flux e, ( - -1/(Z_int+Z_ext)*self.space_cross_h(normal, - Z_ext*(h.ext-h.int) + -1/(Z_int+Z_ext)*self.space_cross_h( + normal, + cast("Vector", Z_ext*(h.ext-h.int)) - self.flux_type*self.space_cross_e(normal, e.ext-e.int)) ), # flux h ( - 1/(Y_int + Y_ext)*self.space_cross_e(normal, - Y_ext*(e.ext-e.int) + 1/(Y_int + Y_ext)*self.space_cross_e( + normal, + cast("Vector", Y_ext*(e.ext-e.int)) + self.flux_type*self.space_cross_h(normal, h.ext-h.int)) ), ) else: raise ValueError(f"maxwell: invalid flux_type ({self.flux_type})") - def local_derivatives(self, w): + def local_derivatives(self, w: Vector) -> Vector: """Template for the spatial derivatives of the relevant components of :math:`E` and :math:`H` """ @@ -322,13 +382,17 @@ def local_derivatives(self, w): [_Dx(self.dcoll, i) for i in range(self.dimensions)] ) - def e_curl(field): - return self.space_cross_e(nabla, field, - three_mult=lambda lc, x, y: lc * (x * y)) + def three_mult( + lc: int, + x: ArrayOrArithContainerOrScalar, + y: ArrayOrArithContainerOrScalar) -> ArrayOrArithContainerOrScalar: + return float(lc) * (x * y) + + def e_curl(field: Vector) -> Vector: + return self.space_cross_e(nabla, field, three_mult=three_mult) # pyright: ignore[reportArgumentType] - def h_curl(field): - return self.space_cross_h(nabla, field, - three_mult=lambda lc, x, y: lc * (x * y)) + def h_curl(field: Vector) -> Vector: + return self.space_cross_h(nabla, field, three_mult=three_mult) # pyright: ignore[reportArgumentType] # in conservation form: u_t + A u_x = 0 return obj_array.flat( @@ -336,8 +400,8 @@ def h_curl(field): e_curl(e) ) - def pec_bc(self, w): - """Construct part of the flux operator template for PEC boundary conditions + def pec_bc(self, w: Vector) -> Vector: + """Construct part of the flux operator template for PEC boundary conditions. """ e, h = self.split_eh(w) @@ -346,8 +410,8 @@ def pec_bc(self, w): return obj_array.flat(-pec_e, pec_h) - def pmc_bc(self, w): - """Construct part of the flux operator template for PMC boundary conditions + def pmc_bc(self, w: Vector) -> Vector: + """Construct part of the flux operator template for PMC boundary conditions. """ e, h = self.split_eh(w) @@ -356,13 +420,13 @@ def pmc_bc(self, w): return obj_array.flat(pmc_e, -pmc_h) - def absorbing_bc(self, w): + def absorbing_bc(self, w: Vector) -> Vector: """Construct part of the flux operator template for 1st order absorbing boundary conditions. """ actx = get_container_context_recursively(w) - absorb_normal = geo.normal(actx, self.dcoll, dd=self.absorb_tag) + absorb_normal = geo.normal(actx, self.dcoll, as_dofdesc(self.absorb_tag)) e, h = self.split_eh(w) @@ -379,17 +443,19 @@ def absorbing_bc(self, w): absorb_h = op.project(self.dcoll, "vol", self.absorb_tag, h) bc = obj_array.flat( - absorb_e + 1/2*(self.space_cross_h(absorb_normal, self.space_cross_e( - absorb_normal, absorb_e)) + absorb_e + 1/2*(self.space_cross_h( + absorb_normal, + self.space_cross_e(absorb_normal, absorb_e)) - absorb_Z*self.space_cross_h(absorb_normal, absorb_h)), absorb_h + 1/2*( - self.space_cross_e(absorb_normal, self.space_cross_h( - absorb_normal, absorb_h)) + self.space_cross_e( + absorb_normal, + self.space_cross_h(absorb_normal, absorb_h)) + absorb_Y*self.space_cross_e(absorb_normal, absorb_e))) return bc - def incident_bc(self, w): + def incident_bc(self, w: Vector) -> Vector: """Flux terms for incident boundary conditions""" # NOTE: Untested for inhomogeneous materials, but would usually be # physically meaningless anyway (are there exceptions to this?) @@ -403,7 +469,7 @@ def incident_bc(self, w): else: return -incident_bc_data - def operator(self, t, w): + def operator(self, t: float, w: Vector) -> Vector: """The full operator template - the high level description of the Maxwell operator. @@ -415,8 +481,7 @@ def operator(self, t, w): if self.fixed_material: # need to check this - material_divisor = ( - [self.epsilon]*elec_components+[self.mu]*mag_components) + material_divisor = [self.epsilon]*elec_components+[self.mu]*mag_components else: raise NotImplementedError("only fixed material supported for now") @@ -429,11 +494,9 @@ def operator(self, t, w): dcoll = self.dcoll - def flux(pair): + def flux(pair: TracePair[Vector]) -> Vector: return op.project(dcoll, pair.dd, "all_faces", self.flux(pair)) - from grudge.dof_desc import as_dofdesc - return ( - self.local_derivatives(w) - op.inverse_mass( @@ -448,7 +511,7 @@ def flux(pair): ) / material_divisor @memoize_method - def partial_to_eh_subsets(self): + def partial_to_eh_subsets(self) -> tuple[VectorIndex, VectorIndex]: """Helps find the indices of the E and H components, which can vary depending on number of dimensions and whether we have a full/TE/TM operator. @@ -457,9 +520,18 @@ def partial_to_eh_subsets(self): e_subset = self.get_eh_subset()[0:3] h_subset = self.get_eh_subset()[3:6] - return tuple(partial_to_all_subset_indices([e_subset, h_subset])) + e_subset, h_subset = partial_to_all_subset_indices([e_subset, h_subset]) + return e_subset, h_subset + + @overload + def split_eh(self, w: Vector) -> tuple[Vector, Vector]: ... + + @overload + def split_eh(self, w: TracePair[Vector]) -> tuple[TracePair[Vector], TracePair[Vector]]: ... # noqa: E501 - def split_eh(self, w): + def split_eh( + self, w: Vector | TracePair[Vector] + ) -> tuple[Vector, Vector] | tuple[TracePair[Vector], TracePair[Vector]]: """Splits an array into E and H components""" e_idx, h_idx = self.partial_to_eh_subsets() e, h = w[e_idx], w[h_idx] @@ -471,16 +543,19 @@ def get_eh_subset(self) -> tuple[bool, bool, bool, bool, bool, bool]: components are to be computed. The fields are numbered in the order specified in the class documentation. """ - return 6*(True,) + return (True, True, True, True, True, True) - def max_characteristic_velocity(self, actx, **kwargs): + @override + def max_characteristic_velocity( + self, actx: ArrayContext, **kwargs: Any + ) -> Array: if self.fixed_material: return 1/np.sqrt(self.epsilon*self.mu) # a number else: return op.nodal_max(self.dcoll, "vol", 1 / actx.np.sqrt(self.epsilon * self.mu)) - def check_bc_coverage(self, mesh): + def check_bc_coverage(self, mesh: Mesh) -> None: from meshmode.mesh import check_bc_coverage check_bc_coverage(mesh, [ self.pec_tag, @@ -497,15 +572,15 @@ def check_bc_coverage(self, mesh): class TMMaxwellOperator(MaxwellOperator): """A 2D TM Maxwell operator with PEC boundaries. - Field order is [Ez Hx Hy]. + Field order is :math:`[E_z, H_x, H_y]`. """ - _default_dimensions = 2 + _default_dimensions: ClassVar[int] = 2 - def get_eh_subset(self): - return ( - (False, False, True, True, True, False) # ez, hx and hy - ) + @override + def get_eh_subset(self) -> tuple[bool, bool, bool, bool, bool, bool]: + # ez hx hy + return (False, False, True, True, True, False) # }}} @@ -515,15 +590,15 @@ def get_eh_subset(self): class TEMaxwellOperator(MaxwellOperator): """A 2D TE Maxwell operator. - Field order is [Ex Ey Hz]. + Field order is :math:`[E_x, E_y, H_z]`. """ - _default_dimensions = 2 + _default_dimensions: ClassVar[int] = 2 - def get_eh_subset(self): - return ( - (True, True, False, False, False, True) # ex and ey, only hz - ) + @override + def get_eh_subset(self) -> tuple[bool, bool, bool, bool, bool, bool]: + # ex ey hz + return (True, True, False, False, False, True) # }}} @@ -533,15 +608,15 @@ def get_eh_subset(self): class TE1DMaxwellOperator(MaxwellOperator): """A 1D TE Maxwell operator. - Field order is [Ex Ey Hz]. + Field order is :math:`[E_x, E_y, H_z]`. """ - _default_dimensions = 1 + _default_dimensions: ClassVar[int] = 1 - def get_eh_subset(self): - return ( - (True, True, False, False, False, True) - ) + @override + def get_eh_subset(self) -> tuple[bool, bool, bool, bool, bool, bool]: + # ex ey hz + return (True, True, False, False, False, True) # }}} @@ -551,42 +626,42 @@ def get_eh_subset(self): class SourceFree1DMaxwellOperator(MaxwellOperator): """A 1D TE Maxwell operator. - Field order is [Ey Hz]. + Field order is :math:`[E_y, H_z]`. """ - _default_dimensions = 1 + _default_dimensions: ClassVar[int] = 1 - def get_eh_subset(self): - return ( - (False, True, False, False, False, True) - ) + @override + def get_eh_subset(self) -> tuple[bool, bool, bool, bool, bool, bool]: + # ey hz + return (False, True, False, False, False, True) # }}} # {{{ get_rectangular_cavity_mode -def get_rectangular_cavity_mode(actx, nodes, t, E_0, mode_indices): # noqa: N803 +def get_rectangular_cavity_mode( + actx: ArrayContext, + nodes: Vector, + t: int | float, + E_0: ArrayOrArithContainerOrScalar, # noqa: N803 + mode_indices: Sequence[int]) -> Vector: """A rectangular TM cavity mode for a rectangle / cube - with one corner at the origin and the other at (1,1[,1]).""" + with one corner at the origin and the other at :math:`(1, 1[, 1])`. + """ dims = len(mode_indices) if dims != 2 and dims != 3: - raise ValueError("Improper mode_indices dimensions") + raise ValueError(f"unsupported 'mode_indices' dimensions: {dims}") factors = [n*np.pi for n in mode_indices] - - kx, ky = factors[0:2] - if dims == 3: - kz = factors[2] - omega = np.sqrt(sum(f**2 for f in factors)) x = nodes[0] y = nodes[1] - if dims == 3: - z = nodes[2] + kx, ky = factors[0:2] - zeros = 0*x + zeros = actx.np.zeros_like(x) sx = actx.np.sin(kx*x) cx = actx.np.cos(kx*x) sy = actx.np.sin(ky*y) @@ -596,16 +671,19 @@ def get_rectangular_cavity_mode(actx, nodes, t, E_0, mode_indices): # noqa: N80 tfac = t * omega result = obj_array.flat( - zeros, - zeros, - actx.np.sin(kx * x) * actx.np.sin(ky * y) * np.cos(tfac), # ez + zeros, # ex + zeros, # ey + actx.np.sin(kx * x) * actx.np.sin(ky * y) * np.cos(tfac), # ez (-ky * actx.np.sin(kx * x) * actx.np.cos(ky * y) - * np.sin(tfac) / omega), # hx + * np.sin(tfac) / omega), # hx (kx * actx.np.cos(kx * x) * actx.np.sin(ky * y) - * np.sin(tfac) / omega), # hy - zeros, + * np.sin(tfac) / omega), # hy + zeros, # hz ) elif dims == 3: + kz = factors[2] + z = nodes[2] + sz = actx.np.sin(kz*z) cz = actx.np.cos(kz*z) @@ -613,15 +691,15 @@ def get_rectangular_cavity_mode(actx, nodes, t, E_0, mode_indices): # noqa: N80 gamma_squared = ky**2 + kx**2 result = obj_array.flat( - -kx * kz * E_0*cx*sy*sz*tdep / gamma_squared, # ex - -ky * kz * E_0*sx*cy*sz*tdep / gamma_squared, # ey - E_0 * sx*sy*cz*tdep, # ez - -1j * omega * ky*E_0*sx*cy*cz*tdep / gamma_squared, # hx - 1j * omega * kx*E_0*cx*sy*cz*tdep / gamma_squared, - zeros, + -kx * kz * E_0*cx*sy*sz*tdep / gamma_squared, # ex + -ky * kz * E_0*sx*cy*sz*tdep / gamma_squared, # ey + E_0 * sx*sy*cz*tdep, # ez + -1j * omega * ky*E_0*sx*cy*cz*tdep / gamma_squared, # hx + 1j * omega * kx*E_0*cx*sy*cz*tdep / gamma_squared, # hy + zeros, # hz ) else: - raise NotImplementedError("only 2D and 3D supported") + raise NotImplementedError(f"only 2D and 3D supported: dim = {dims}") return result diff --git a/grudge/op.py b/grudge/op.py index 339a29ca..7cf607a4 100644 --- a/grudge/op.py +++ b/grudge/op.py @@ -53,7 +53,7 @@ """ from functools import partial -from typing import TYPE_CHECKING, Any, cast +from typing import TYPE_CHECKING, Any, cast, overload import numpy as np @@ -64,7 +64,6 @@ ArrayContainer, ArrayContainerT, ArrayContext, - ArrayOrContainer, ArrayOrContainerOrScalar, is_array_container, map_array_container, @@ -73,6 +72,7 @@ from arraycontext.typing import is_scalar_like from meshmode.discretization import ( InterpolatoryElementGroupBase, + NodalElementGroupBase, ) from meshmode.dof_array import DOFArray from meshmode.transform_metadata import ( @@ -83,11 +83,10 @@ ) from pytools import keyed_memoize_in -import grudge.dof_desc as dof_desc from grudge.dof_desc import ( DD_VOLUME_ALL, DISCR_TAG_BASE, - FACE_RESTR_ALL, + FACE_RESTR_ALL, # pyright: ignore[reportPrivateLocalImportUsage] BoundaryDomainTag, DOFDesc, ToDOFDescConvertible, @@ -126,10 +125,13 @@ if TYPE_CHECKING: from collections.abc import Callable, Hashable + # NOTE: do not be tempted to move this import out of TYPE_CHECKING: doing so + # makes sphinx *sometimes* expand the type alias and fail due to some types + # that are not actually documented (e.g. _UserDefinedArrayContainer) + from arraycontext import ArrayOrContainer from meshmode.discretization import ( Discretization, ElementGroupBase, - NodalElementGroupBase, ) from grudge.discretization import DiscretizationCollection @@ -177,12 +179,13 @@ def _single_axis_derivative_kernel( actx: ArrayContext, out_discr: Discretization, in_discr: Discretization, - get_diff_mat, - inv_jac_mat, + get_diff_mat: Callable[[ArrayContext, ElementGroupBase, ElementGroupBase], + Array], + inv_jac_mat: DOFArray, xyz_axis: int, vec: DOFArray, *, - metric_in_matvec: bool): + metric_in_matvec: bool) -> DOFArray: # This gets used from both the strong and the weak derivative. These differ # in three ways: # - which differentiation matrix gets used, @@ -197,10 +200,7 @@ def _single_axis_derivative_kernel( # r for rst axis actx.einsum("rej,rij,ej->ei" if metric_in_matvec else "rei,rij,ej->ei", ijm_i[xyz_axis], - get_diff_mat( - actx, - out_element_group=out_grp, - in_element_group=in_grp), + get_diff_mat(actx, out_grp, in_grp), vec_i, arg_names=("inv_jac_t", "ref_stiffT_mat", "vec", ), tagged=(FirstAxisIsElementsTag(),)) @@ -216,11 +216,12 @@ def _gradient_kernel( actx: ArrayContext, out_discr: Discretization, in_discr: Discretization, - get_diff_mat, - inv_jac_mat, + get_diff_mat: Callable[[ArrayContext, ElementGroupBase, ElementGroupBase], + Array], + inv_jac_mat: DOFArray, vec: DOFArray, *, - metric_in_matvec: bool): + metric_in_matvec: bool) -> obj_array.ObjectArray1D[DOFArray]: # See _single_axis_derivative_kernel for comments on the usage scenarios # (both strong and weak derivative) and their differences. per_group_grads = [ @@ -228,11 +229,7 @@ def _gradient_kernel( # x for xyz axis actx.einsum("xrej,rij,ej->xei" if metric_in_matvec else "xrei,rij,ej->xei", ijm_i, - get_diff_mat( - actx, - out_element_group=out_grp, - in_element_group=in_grp - ), + get_diff_mat(actx, out_grp, in_grp), vec_i, arg_names=("inv_jac_t", "ref_stiffT_mat", "vec"), tagged=(FirstAxisIsElementsTag(),)) @@ -251,11 +248,12 @@ def _divergence_kernel( actx: ArrayContext, out_discr: Discretization, in_discr: Discretization, - get_diff_mat, - inv_jac_mat, + get_diff_mat: Callable[[ArrayContext, ElementGroupBase, ElementGroupBase], + Array], + inv_jac_mat: DOFArray, vec: DOFArray, *, - metric_in_matvec: bool): + metric_in_matvec: bool) -> DOFArray: # See _single_axis_derivative_kernel for comments on the usage scenarios # (both strong and weak derivative) and their differences. per_group_divs = [ @@ -263,11 +261,7 @@ def _divergence_kernel( # x for xyz axis actx.einsum("xrej,rij,xej->ei" if metric_in_matvec else "xrei,rij,xej->ei", ijm_i, - get_diff_mat( - actx, - out_element_group=out_grp, - in_element_group=in_grp - ), + get_diff_mat(actx, out_grp, in_grp), vec_i, arg_names=("inv_jac_t", "ref_stiffT_mat", "vec"), tagged=(FirstAxisIsElementsTag(),)) @@ -284,16 +278,21 @@ def _divergence_kernel( # {{{ Derivative operators -def _reference_derivative_matrices(actx: ArrayContext, - out_element_group: NodalElementGroupBase, - in_element_group: InterpolatoryElementGroupBase) -> Array: +def _reference_derivative_matrices( + actx: ArrayContext, + out_element_group: ElementGroupBase, + in_element_group: ElementGroupBase, /) -> Array: + if not isinstance(out_element_group, NodalElementGroupBase): + raise TypeError(f"'out_element_group' must be nodal: {type(out_element_group)}") + + if not isinstance(in_element_group, InterpolatoryElementGroupBase): + raise TypeError( + f"'in_element_group' must be interpolatory: {type(in_element_group)}") def memoize_key( out_grp: NodalElementGroupBase, in_grp: InterpolatoryElementGroupBase ) -> Hashable: - return ( - out_grp.discretization_key(), - in_grp.discretization_key()) + return out_grp.discretization_key(), in_grp.discretization_key() @keyed_memoize_in( actx, _reference_derivative_matrices, @@ -311,28 +310,38 @@ def get_ref_derivative_mats( out_grp.unit_nodes, from_nodes=in_grp.unit_nodes, ))))) + return get_ref_derivative_mats(out_element_group, in_element_group) -def _strong_scalar_grad(dcoll, dd_in, vec): +def _strong_scalar_grad( + dcoll: DiscretizationCollection, dd_in: DOFDesc, vec: ArrayOrContainer + ) -> obj_array.ObjectArray1D[DOFArray]: assert isinstance(dd_in.domain_tag, VolumeDomainTag) + assert isinstance(vec, DOFArray) from grudge.geometry import inverse_surface_metric_derivative_mat discr = dcoll.discr_from_dd(dd_in) actx = vec.array_context + assert actx is not None - inverse_jac_mat = inverse_surface_metric_derivative_mat(actx, dcoll, dd=dd_in, + inverse_jac_mat = inverse_surface_metric_derivative_mat( + actx, dcoll, dd=dd_in, _use_geoderiv_connection=actx.supports_nonscalar_broadcasting) - return _gradient_kernel(actx, discr, discr, - _reference_derivative_matrices, inverse_jac_mat, vec, + + return _gradient_kernel( + actx, discr, discr, + _reference_derivative_matrices, + inverse_jac_mat, + vec, metric_in_matvec=False) def _strong_scalar_div( dcoll: DiscretizationCollection, dd: DOFDesc, - vecs: obj_array.ObjectArray1D[DOFArray]): + vecs: obj_array.ObjectArray1D[DOFArray]) -> DOFArray: from arraycontext import get_container_context_recursively from grudge.geometry import inverse_surface_metric_derivative_mat @@ -353,9 +362,23 @@ def _strong_scalar_div( metric_in_matvec=False) +@overload +def local_grad( + dcoll: DiscretizationCollection, vec: ArrayOrContainer, /, *, + nested: bool = False, +) -> ArrayOrContainer: ... + + +@overload +def local_grad( + dcoll: DiscretizationCollection, dd_in: DOFDesc, vec: ArrayOrContainer, /, *, + nested: bool = False, +) -> ArrayOrContainer: ... + + def local_grad( dcoll: DiscretizationCollection, - *args, + *args: Any, nested: bool = False) -> ArrayOrContainer: r"""Return the element-local gradient of a function :math:`f` represented by *vec*: @@ -392,8 +415,23 @@ def local_grad( vec, scalar_cls=DOFArray, return_nested=nested,) +@overload +def local_d_dx( + dcoll: DiscretizationCollection, xyz_axis: int, + vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +@overload +def local_d_dx( + dcoll: DiscretizationCollection, xyz_axis: int, + dd: DOFDesc, vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + def local_d_dx( - dcoll: DiscretizationCollection, xyz_axis: int, *args) -> ArrayOrContainer: + dcoll: DiscretizationCollection, xyz_axis: int, + *args: Any) -> ArrayOrContainer: r"""Return the element-local derivative along axis *xyz_axis* of a function :math:`f` represented by *vec*: @@ -418,7 +456,7 @@ def local_d_dx( elif len(args) == 2: dd, vec = args else: - raise TypeError("invalid number of arguments") + raise TypeError(f"invalid number of arguments to 'local_d_dx': {len(args)}") if not isinstance(vec, DOFArray): return map_array_container(partial(local_d_dx, dcoll, xyz_axis, dd), vec) @@ -437,7 +475,19 @@ def local_d_dx( metric_in_matvec=False) -def local_div(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: +@overload +def local_div( + dcoll: DiscretizationCollection, vecs: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +@overload +def local_div( + dcoll: DiscretizationCollection, dd: DOFDesc, vecs: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +def local_div(dcoll: DiscretizationCollection, *args: Any) -> ArrayOrContainer: r"""Return the element-local divergence of the vector function :math:`\mathbf{f}` represented by *vecs*: @@ -478,15 +528,26 @@ def local_div(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: def _reference_stiffness_transpose_matrices( actx: ArrayContext, - out_element_group: InterpolatoryElementGroupBase, - in_element_group: InterpolatoryElementGroupBase): + out_element_group: ElementGroupBase, + in_element_group: ElementGroupBase) -> Array: + if not isinstance(out_element_group, InterpolatoryElementGroupBase): + raise TypeError( + f"'out_element_group' must be interpolatory: {type(out_element_group)}") + + if not isinstance(in_element_group, NodalElementGroupBase): + raise TypeError( + f"'in_element_group' must be nodal: {type(in_element_group)}") + + def memoize_key(out_grp: InterpolatoryElementGroupBase, + in_grp: NodalElementGroupBase) -> Hashable: + return out_grp.discretization_key(), in_grp.discretization_key() + @keyed_memoize_in( actx, _reference_stiffness_transpose_matrices, - lambda out_grp, in_grp: (out_grp.discretization_key(), - in_grp.discretization_key())) + memoize_key) def get_ref_stiffness_transpose_mat( out_grp: InterpolatoryElementGroupBase, - in_grp: InterpolatoryElementGroupBase): + in_grp: NodalElementGroupBase) -> Array: if in_grp == out_grp: mmat = mp.mass_matrix(out_grp.basis_obj(), out_grp.unit_nodes) diff_matrices = mp.diff_matrices(out_grp.basis_obj(), out_grp.unit_nodes) @@ -522,7 +583,11 @@ def get_ref_stiffness_transpose_mat( in_element_group) -def _weak_scalar_grad(dcoll, dd_in, vec): +def _weak_scalar_grad( + dcoll: DiscretizationCollection, dd_in: DOFDesc, vec: ArrayOrContainer + ) -> obj_array.ObjectArray1D[ArrayOrContainer]: + assert isinstance(vec, DOFArray) + from grudge.geometry import inverse_surface_metric_derivative_mat dd_in = as_dofdesc(dd_in) @@ -530,6 +595,8 @@ def _weak_scalar_grad(dcoll, dd_in, vec): out_discr = dcoll.discr_from_dd(dd_in.with_discr_tag(DISCR_TAG_BASE)) actx = vec.array_context + assert actx is not None + inverse_jac_mat = inverse_surface_metric_derivative_mat(actx, dcoll, dd=dd_in, times_area_element=True, _use_geoderiv_connection=actx.supports_nonscalar_broadcasting) @@ -542,7 +609,7 @@ def _weak_scalar_grad(dcoll, dd_in, vec): def _weak_scalar_div( dcoll: DiscretizationCollection, dd_in: DOFDesc, - vecs: obj_array.ObjectArray1D[DOFArray]): + vecs: obj_array.ObjectArray1D[DOFArray]) -> DOFArray: from arraycontext import get_container_context_recursively from grudge.geometry import inverse_surface_metric_derivative_mat @@ -565,8 +632,23 @@ def _weak_scalar_div( metric_in_matvec=True) +@overload +def weak_local_grad( + dcoll: DiscretizationCollection, vec: ArrayOrContainer, /, *, + nested: bool = False, +) -> ArrayOrContainer: ... + + +@overload def weak_local_grad( - dcoll: DiscretizationCollection, *args, nested=False) -> ArrayOrContainer: + dcoll: DiscretizationCollection, dd_in: DOFDesc, vec: ArrayOrContainer, /, *, + nested: bool = False, +) -> ArrayOrContainer: ... + + +def weak_local_grad( + dcoll: DiscretizationCollection, + *args: Any, nested: bool = False) -> ArrayOrContainer: r"""Return the element-local weak gradient of the volume function represented by *vec*. @@ -603,7 +685,21 @@ def weak_local_grad( vecs, scalar_cls=DOFArray, return_nested=nested) -def weak_local_d_dx(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: +@overload +def weak_local_d_dx( + dcoll: DiscretizationCollection, + xyz_axis: int, vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +@overload +def weak_local_d_dx( + dcoll: DiscretizationCollection, + dd_in: DOFDesc, xyz_axis: int, vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +def weak_local_d_dx(dcoll: DiscretizationCollection, *args: Any) -> ArrayOrContainer: r"""Return the element-local weak derivative along axis *xyz_axis* of the volume function represented by *vec*. @@ -635,7 +731,7 @@ def weak_local_d_dx(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: """ if len(args) == 2: xyz_axis, vec = args - dd_in = dof_desc.DD_VOLUME_ALL + dd_in = DD_VOLUME_ALL elif len(args) == 3: dd_in, xyz_axis, vec = args else: @@ -665,7 +761,21 @@ def weak_local_d_dx(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: metric_in_matvec=True) -def weak_local_div(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: +@overload +def weak_local_div( + dcoll: DiscretizationCollection, + vecs: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +@overload +def weak_local_div( + dcoll: DiscretizationCollection, + dd: DOFDesc, vecs: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +def weak_local_div(dcoll: DiscretizationCollection, *args: Any) -> ArrayOrContainer: r"""Return the element-local weak divergence of the vector volume function represented by *vecs*. @@ -713,12 +823,26 @@ def weak_local_div(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: # {{{ Mass operator -def reference_mass_matrix(actx: ArrayContext, out_element_group, in_element_group): +def reference_mass_matrix( + actx: ArrayContext, + out_element_group: ElementGroupBase, + in_element_group: ElementGroupBase) -> Array: + if not isinstance(out_element_group, InterpolatoryElementGroupBase): + raise TypeError( + f"'out_element_group' must be interpolatory: {type(out_element_group)}") + + if not isinstance(in_element_group, NodalElementGroupBase): + raise TypeError(f"'in_element_group' must be nodal: {type(in_element_group)}") + + def memoize_key(out_grp: InterpolatoryElementGroupBase, + in_grp: NodalElementGroupBase) -> Hashable: + return out_grp.discretization_key(), in_grp.discretization_key() + @keyed_memoize_in( actx, reference_mass_matrix, - lambda out_grp, in_grp: (out_grp.discretization_key(), - in_grp.discretization_key())) - def get_ref_mass_mat(out_grp, in_grp): + memoize_key) + def get_ref_mass_mat(out_grp: InterpolatoryElementGroupBase, + in_grp: NodalElementGroupBase): if out_grp == in_grp: return actx.freeze( actx.from_numpy( @@ -750,7 +874,7 @@ def _apply_mass_operator( vec: ArrayContainerT ) -> ArrayContainerT: if is_scalar_like(vec): - raise TypeError("scalars not allowed") + raise TypeError(f"scalars not allowed: {vec}") if not isinstance(vec, DOFArray): result = map_array_container( @@ -793,7 +917,21 @@ def _apply_mass_operator( ) -def mass(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: +@overload +def mass( + dcoll: DiscretizationCollection, + vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +@overload +def mass( + dcoll: DiscretizationCollection, + dd_in: DOFDesc, vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +def mass(dcoll: DiscretizationCollection, *args: Any) -> ArrayOrContainer: r"""Return the action of the DG mass matrix on a vector (or vectors) of :class:`~meshmode.dof_array.DOFArray`\ s, *vec*. In the case of *vec* being an :class:`~arraycontext.ArrayContainer`, @@ -821,7 +959,7 @@ def mass(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: if len(args) == 1: vec, = args - dd_in = dof_desc.DD_VOLUME_ALL + dd_in = DD_VOLUME_ALL elif len(args) == 2: dd_in, vec = args else: @@ -836,11 +974,19 @@ def mass(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: # {{{ Mass inverse operator -def reference_inverse_mass_matrix(actx: ArrayContext, element_group): +def reference_inverse_mass_matrix( + actx: ArrayContext, element_group: ElementGroupBase + ) -> Array: + if not isinstance(element_group, InterpolatoryElementGroupBase): + raise TypeError(f"'element_group' must be interpolatory: {type(element_group)}") + + def memoize_key(grp: InterpolatoryElementGroupBase) -> Hashable: + return grp.discretization_key() + @keyed_memoize_in( actx, reference_inverse_mass_matrix, - lambda grp: grp.discretization_key()) - def get_ref_inv_mass_mat(grp): + memoize_key) + def get_ref_inv_mass_mat(grp: InterpolatoryElementGroupBase) -> Array: from modepy import inverse_mass_matrix basis = grp.basis_obj() @@ -894,7 +1040,21 @@ def _apply_inverse_mass_operator( return DOFArray(actx, data=tuple(group_data)) -def inverse_mass(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: +@overload +def inverse_mass( + dcoll: DiscretizationCollection, + vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +@overload +def inverse_mass( + dcoll: DiscretizationCollection, + dd: DOFDesc, vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +def inverse_mass(dcoll: DiscretizationCollection, *args: Any) -> ArrayOrContainer: r"""Return the action of the DG mass matrix inverse on a vector (or vectors) of :class:`~meshmode.dof_array.DOFArray`\ s, *vec*. In the case of *vec* being an :class:`~arraycontext.ArrayContainer`, @@ -950,13 +1110,20 @@ def inverse_mass(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: def reference_face_mass_matrix( actx: ArrayContext, - face_element_group: InterpolatoryElementGroupBase, - vol_element_group: InterpolatoryElementGroupBase, - dtype: np.dtype[Any]): + face_element_group: ElementGroupBase, + vol_element_group: ElementGroupBase, + dtype: np.dtype[Any]) -> Array: + if not isinstance(vol_element_group, InterpolatoryElementGroupBase): + raise TypeError( + f"'vol_element_group' must be interpolatory: {type(vol_element_group)}") + + def memoize_key(face_grp: ElementGroupBase, + vol_grp: InterpolatoryElementGroupBase) -> Hashable: + return face_grp.discretization_key(), vol_grp.discretization_key() + @keyed_memoize_in( actx, reference_mass_matrix, - lambda face_grp, vol_grp: (face_grp.discretization_key(), - vol_grp.discretization_key())) + memoize_key) def get_ref_face_mass_mat( face_grp: ElementGroupBase, vol_grp: InterpolatoryElementGroupBase): @@ -1045,7 +1212,7 @@ def get_ref_face_mass_mat( def _apply_face_mass_operator( dcoll: DiscretizationCollection, dd_in: DOFDesc, - vec: DOFArray): + vec: ArrayOrContainer) -> ArrayOrContainer: if not isinstance(vec, DOFArray): return map_array_container( partial(_apply_face_mass_operator, dcoll, dd_in), vec @@ -1100,7 +1267,21 @@ def _apply_face_mass_operator( strict=True))) -def face_mass(dcoll: DiscretizationCollection, *args) -> ArrayOrContainer: +@overload +def face_mass( + dcoll: DiscretizationCollection, + vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +@overload +def face_mass( + dcoll: DiscretizationCollection, + dd: DOFDesc, vec: ArrayOrContainer, /, +) -> ArrayOrContainer: ... + + +def face_mass(dcoll: DiscretizationCollection, *args: Any) -> ArrayOrContainer: r"""Return the action of the DG face mass matrix on a vector (or vectors) of :class:`~meshmode.dof_array.DOFArray`\ s, *vec*. In the case of *vec* being an arbitrary :class:`~arraycontext.ArrayContainer`, diff --git a/grudge/trace_pair.py b/grudge/trace_pair.py index d6377f7d..fb0b1191 100644 --- a/grudge/trace_pair.py +++ b/grudge/trace_pair.py @@ -54,7 +54,7 @@ from dataclasses import dataclass from numbers import Number -from typing import TYPE_CHECKING, ClassVar, Generic, cast +from typing import TYPE_CHECKING, ClassVar, Generic, TypeAlias, cast, overload from warnings import warn import numpy as np @@ -80,7 +80,7 @@ from grudge.dof_desc import ( DD_VOLUME_ALL, DISCR_TAG_BASE, - FACE_RESTR_INTERIOR, + FACE_RESTR_INTERIOR, # pyright: ignore[reportPrivateLocalImportUsage] BoundaryDomainTag, DiscretizationTag, DOFDesc, @@ -104,6 +104,9 @@ # {{{ trace pair container class +Index: TypeAlias = np.ndarray[tuple[int, ...], np.dtype[np.integer]] + + @with_container_arithmetic(bcasts_across_obj_array=False, eq_comparison=False, rel_comparison=False, @@ -114,15 +117,11 @@ class TracePair(Generic[ArithArrayContainerT]): """A container class for data (both interior and exterior restrictions) on the boundaries of mesh elements. - .. attribute:: dd - - an instance of :class:`grudge.dof_desc.DOFDesc` describing the - discretization on which :attr:`int` and :attr:`ext` live. - - .. autoattribute:: int - .. autoattribute:: ext - .. autoattribute:: avg - .. autoattribute:: diff + .. autoattribute:: dd + .. autoproperty:: int + .. autoproperty:: ext + .. autoproperty:: avg + .. autoproperty:: diff .. automethod:: __getattr__ .. automethod:: __getitem__ @@ -130,6 +129,10 @@ class TracePair(Generic[ArithArrayContainerT]): """ dd: DOFDesc + """An instance of :class:`~grudge.dof_desc.DOFDesc` describing the + discretization on which :attr:`int` and :attr:`ext` live. + """ + interior: ArithArrayContainerT exterior: ArithArrayContainerT @@ -145,6 +148,7 @@ def __init__(self, dd: DOFDesc, *, "This will stop working in December 2022. " "Pass an actual DOFDesc instead.", DeprecationWarning, stacklevel=2) + dd = dof_desc.as_dofdesc(dd) object.__setattr__(self, "dd", dd) @@ -159,18 +163,24 @@ def __getattr__(self, name: str) -> TracePair[ArithArrayContainer]: interior=getattr(self.interior, name), exterior=getattr(self.exterior, name)) - def __getitem__(self, index: int | slice) -> TracePair[ArithArrayContainer]: + @overload + def __getitem__(self, index: int) -> TracePair[ArithArrayContainer]: ... + + @overload + def __getitem__(self, index: slice | Index) -> TracePair[ArithArrayContainerT]: ... + + def __getitem__( + self, index: int | slice | Index + ) -> TracePair[ArithArrayContainer]: """Return a new :class:`TracePair` resulting from executing subscripting with *index* on :attr:`int` and :attr:`ext`. """ return TracePair(self.dd, - interior=cast( - "SupportsGetItem[int | slice, ArithArrayContainer]", - self.interior)[index], - exterior=cast( - "SupportsGetItem[int | slice, ArithArrayContainer]", - self.exterior)[index] - ) + interior=cast("SupportsGetItem[int | slice | Index, ArithArrayContainer]", + self.interior)[index], + exterior=cast("SupportsGetItem[int | slice | Index, ArithArrayContainer]", + self.exterior)[index] + ) def __len__(self): """Return the total number of arrays associated with the diff --git a/test/test_grudge.py b/test/test_grudge.py index f930f32f..244abd62 100644 --- a/test/test_grudge.py +++ b/test/test_grudge.py @@ -906,7 +906,7 @@ def rhs(t, u, adv_operator=adv_operator): # {{{ models: maxwell @pytest.mark.parametrize("order", [3, 4, 5]) -def test_convergence_maxwell(actx_factory: ArrayContextFactory, order): +def test_convergence_maxwell(actx_factory: ArrayContextFactory, order: int) -> None: """Test whether 3D Maxwell's actually converges""" actx = actx_factory() @@ -927,9 +927,9 @@ def test_convergence_maxwell(actx_factory: ArrayContextFactory, order): epsilon = 1 mu = 1 - from grudge.models.em import get_rectangular_cavity_mode + from grudge.models.em import Vector, get_rectangular_cavity_mode - def analytic_sol(x, t=0): + def analytic_sol(x: Vector, t: float = 0) -> Vector: return get_rectangular_cavity_mode(actx, x, t, 1, (1, 2, 2)) nodes = actx.thaw(dcoll.nodes()) @@ -946,10 +946,12 @@ def analytic_sol(x, t=0): ) maxwell_operator.check_bc_coverage(mesh) - def rhs(t, w, maxwell_operator=maxwell_operator): + def rhs(t: float, + w: Vector, + maxwell_operator: MaxwellOperator = maxwell_operator) -> Vector: return maxwell_operator.operator(t, w) - dt = actx.to_numpy(maxwell_operator.estimate_rk4_timestep(actx, dcoll)) + dt = actx.to_numpy(maxwell_operator.estimate_rk4_timestep(actx, dcoll)).item() final_t = dt * 5 nsteps = int(final_t/dt) @@ -970,9 +972,11 @@ def rhs(t, w, maxwell_operator=maxwell_operator): step += 1 logger.debug("[%04d] t = %.5e", step, event.t) + assert esc is not None + sol = analytic_sol(nodes, t=step * dt) total_error = op.norm(dcoll, esc - sol, 2) - eoc_rec.add_data_point(1.0/n, actx.to_numpy(total_error)) + eoc_rec.add_data_point(1.0/n, actx.to_numpy(total_error).item()) logger.info("\n%s", eoc_rec.pretty_print( abscissa_label="h",